System for automatic object classification and tagging in an rf planning tool

ABSTRACT

A system and method store a map of an area in a computer storage device. The map includes objects in the area. Objects on the map and locations of the objects on the map are identified, and properties are associated to the identified objects. The identified objects, the locations of the identified objects, and the properties of the identified objects are provided to a radio frequency (RF) planning tool such that the RF planning tool can determine RF wave propagation and RF wave attenuation as a function of the identified objects, the locations of the identified objects, and the properties of the identified objects.

TECHNICAL FIELD

The present disclosure relates to a system for automatic objectclassification and tagging in an RF planning tool.

BACKGROUND

A typical wireless network includes several sensors and one or morecontrollers. A radio frequency (RF) planning tool can be used to assistin the planning and design of such a wireless network. In the situationwherein it is desired to install a wireless network at a typicalindustrial site, such as a petroleum tank farm, such an industrial sitemay have multiple objects of similar characteristics (e.g., tank farmshave clusters of tanks, wooden walls, pipes, and other structures).Consequently, before RF planning, the designer has to identify and placeall the objects in the image and place the objects at appropriatelocations in the site. However, identifying objects in the site map(e.g., an image, CAD drawing, BIM, etc.) may be a time consuming processfor the designer. Moreover, after identifying the objects, the designerneeds to key in the attributes of the objects. This keying in process,once again, is time consuming, and increases the cost and time of an RFwireless network estimation. Furthermore, manual operations mayintroduce errors in the location of the objects as well the size of theobjects.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a process to automate the identificationand classification of objects in an area for use in connection with atool to plan and design wireless radio frequency (RF) networks.

FIGS. 2A and 2B are another block diagram of a process to automate theidentification and classification of objects in an area for use inconnection with a tool to plan and design wireless radio frequency (RF)networks.

FIG. 3 is a diagram of an industrial site.

FIG. 4 is a diagram of the industrial site of FIG. 3 after the objectsat the industrial site have been automatically identified and tagged.

FIG. 5 is another block diagram of a process to automate theidentification and classification of objects in an area for use inconnection with a tool to plan and design wireless radio frequency (RF)networks

FIG. 6 is a block diagram of a computer system upon which an embodimentof the present disclosure can execute.

DETAILED DESCRIPTION

In the following description, reference is made to the accompanyingdrawings that form a part hereof, and in which is shown by way ofillustration specific embodiments which may be practiced. Theseembodiments are described in sufficient detail to enable those skilledin the art to practice the invention, and it is to be understood thatother embodiments may be utilized and that structural, electrical, andoptical changes may be made without departing from the scope of thepresent invention. The following description of example embodiments is,therefore, not to be taken in a limited sense, and the scope of thepresent invention is defined by the appended claims.

One or more embodiments relate to the use of an auto-tagging scheme inconnection with the use of an RF planning tool. Specifically, autoobject identification identifies the objects in the site using patternrecognition, and classifies the objects into various known classes basedon a prior set of collected data. Once similar objects are identified inthe site, they can be associated to a class of materials. Furthermore,once the tool is trained, the tagged objects can be directly identifiedwithout any user intervention. The user can also train the patternrecognition algorithm by giving the shape and/or color of the object asa class. The tool can also use a previously trained set of sequences,such as can be found in an Internet-based map (e.g., Google maps).Additionally, products such as Google Earth can tag and can landmarkvarious structures, and this information can be used for autoidentification of objects for RF planning. Similarly, some data formatslike CAD and BIM include site specific details, which can be useddirectly in an RF planning tool without having to do any auto detection.Irrespective of the origin of the data, based on the base lineshape/color combination, the tool can automatically identify and locatethe objects in the site. This process automates the site specificmaterial placement in the tool and can simplify the RF pre-planningprocess. A high level block diagram of the process is illustrated inFIG. 1.

A more detailed explanation of this process 200 is illustrated in FIGS.2A and 2B. FIGS. 2A and 2B include a number of process blocks 205-285.Though arranged serially in the example of FIGS. 2A and 2B, otherexamples may reorder the blocks, omit one or more blocks, and/or executetwo or more blocks in parallel using multiple processors or a singleprocessor organized as two or more virtual machines or sub-processors.Moreover, still other examples can implement the blocks as one or morespecific interconnected hardware or integrated circuit modules withrelated control and data signals communicated between and through themodules. Thus, any process flow is applicable to software, firmware,hardware, and hybrid implementations.

Referring to FIGS. 2A and 2B, at 205 a floor plan map or a site map isimported into a computer processor and/or computer storage medium. Thismap can be a computer aided design (CAD) image, a building informationmodel (BIM) image, or an image in some other format. An example of sucha site plan for an industrial petroleum tank site is illustrated in FIG.3. FIG. 3 illustrates a tank farm 300, which includes buildings 310,tanks 320, and pipelines 330. At 210, a user provides a pattern toidentify an object in the floor or site plan. This pattern can be from apattern library, it can be from an Internet-based map, or it can be fromCAD or BIM data. The pattern can also be a small image segment providedby the user. At 215, the process 200 automatically identifies theobjects based on the pattern input by the user. Alternatively, a taggingrule can be applied to the floor or site plan to identify the objects inthe site plan. FIG. 4 illustrates the tagging of the identified objectswith icons. The tagging in FIG. 4 is illustrated by dashed lines aroundbuildings 310, dashed lines around tanks 320, and diagonal lines withinthe pipelines 330. At 220, the process 200 associates properties withthe identified object. The properties of an object, such as a thicknessand material of a wall of a building or a size and material of apipeline, can be stored in a database. At 225, after the tagging ofobjects and the association of properties of the objects, a user canmanually adjust the location and/or properties of the objects. At 230,data relating to the tagging of objects and the properties of theobjects are provided to a wireless RF planning tool. The planning toolcan then use this data in its planning and design of a wireless networkfor the floor plan or site plan. Specifically, the planning tool candetermine the placement of sensors and transmitters based on wavepropagation and wave attenuation caused by the objects in the floor orsite plan.

At 235, the RF planning tool uses the identified objects, the locationsof the identified objects, and the properties of the identified objectsin a link budget calculation, and at 240, the RF planning tool uses theidentified objects, the locations of the identified objects, and theproperties of the identified objects in a design of a wireless networkfor the area. At 245, the map comprises one or more of computer aideddesign (CAD) data, building information model (BIM) data, Internet-basedmap data, and jpeg data. At 250, the computer processor is configured toreceive input from a user to modify the properties of the identifiedobjects. At 255, the computer processor is configured to identify theobjects by tagging the objects, the tagging comprising associating iconswith the locations of the objects on the map. At 260, the computerprocessor is configured to receive input from a user relating to one ormore of shapes and colors of the objects, and to use the user input toidentify the objects on the map. The user input comprises one or more ofan Internet-based map, a computer aided design (CAD) format with sitespecific details, and a building information model (BIM) format withsite specific details. At 265, the computer processor comprises apattern recognition algorithm to identify the objects. At 270, thecomputer processor comprises a tagging rule to identify the objects. At275, the computer processor is configured to receive input from a userand to use the user input to verify the identified objects. The userinput can include one or more of an Internet-based map, a computer aideddesign (CAD) format with site specific details, and a buildinginformation model (BIM) format with site specific details. At 280, thecomputer processor is configured to classify the identified objects as afunction of one or more of similar objects and similar materials. At285, the computer storage device comprises data relating to the identityof objects and the properties of objects, and the computer processor isconfigured to use the data to identify objects in the area and toassociate properties to the identified objects. At 290, theidentification of the objects and the locations of the objects isautomatic as a function of a maturation of a system that includes thecomputer readable storage device and a learning of patterns by thesystem.

FIG. 5 illustrates another embodiment of a process to automate theidentification and classification of objects in an area for use inconnection with a tool to plan and design wireless radio frequency (RF)networks. At 510, a floor map is imported into a computer processor. Thefloor map can be either a CAD image or a BIM image. At 520, a pattern isset that is used to identify structures and objects in the floor map.Predefined symbols can be obtained from a symbol library, and/or a smallimage segment can be provided by a user. This could also be a legendused in the drawing, e.g., color codes or patterns to represent objectsand definitions. At 530, objects are automatically identified per thegiven input in step 520, or via a predefined tagging rule. At 540,properties for the identified objects are automatically filed. At 550,manual adjustments are made to the identified objects if needed. At 560,the data is fed to an RF algorithm in order to verify the plan.

FIG. 6 is an overview diagram of a hardware and operating environment inconjunction with which embodiments of the invention may be practiced.The description of FIG. 6 is intended to provide a brief, generaldescription of suitable computer hardware and a suitable computingenvironment in conjunction with which the invention may be implemented.In some embodiments, the invention is described in the general contextof computer-executable instructions, such as program modules, beingexecuted by a computer, such as a personal computer. Generally, programmodules include routines, programs, objects, components, datastructures, etc., that perform particular tasks or implement particularabstract data types.

Moreover, those skilled in the art will appreciate that the inventionmay be practiced with other computer system configurations, includinghand-held devices, multiprocessor systems, microprocessor-based orprogrammable consumer electronics, network PCS, minicomputers, mainframecomputers, and the like. The invention may also be practiced indistributed computer environments where tasks are performed by I/Oremote processing devices that are linked through a communicationsnetwork. In a distributed computing environment, program modules may belocated in both local and remote memory storage devices.

In the embodiment shown in FIG. 6, a hardware and operating environmentis provided that is applicable to any of the servers and/or remoteclients shown in the other Figures.

As shown in FIG. 6, one embodiment of the hardware and operatingenvironment includes a general purpose computing device in the form of acomputer 20 (e.g., a personal computer, workstation, or server),including one or more processing units 21, a system memory 22, and asystem bus 23 that operatively couples various system componentsincluding the system memory 22 to the processing unit 21. There may beonly one or there may be more than one processing unit 21, such that theprocessor of computer 20 comprises a single central-processing unit(CPU), or a plurality of processing units, commonly referred to as amultiprocessor or parallel-processor environment. A multiprocessorsystem can include cloud computing environments. In various embodiments,computer 20 is a conventional computer, a distributed computer, or anyother type of computer.

The system bus 23 can be any of several types of bus structuresincluding a memory bus or memory controller, a peripheral bus, and alocal bus using any of a variety of bus architectures. The system memorycan also be referred to as simply the memory, and, in some embodiments,includes read-only memory (ROM) 24 and random-access memory (RAM) 25. Abasic input/output system (BIOS) program 26, containing the basicroutines that help to transfer information between elements within thecomputer 20, such as during start-up, may be stored in ROM 24. Thecomputer 20 further includes a hard disk drive 27 for reading from andwriting to a hard disk, not shown, a magnetic disk drive 28 for readingfrom or writing to a removable magnetic disk 29, and an optical diskdrive 30 for reading from or writing to a removable optical disk 31 suchas a CD ROM or other optical media.

The hard disk drive 27, magnetic disk drive 28, and optical disk drive30 couple with a hard disk drive interface 32, a magnetic disk driveinterface 33, and an optical disk drive interface 34, respectively. Thedrives and their associated computer-readable media provide non volatilestorage of computer-readable instructions, data structures, programmodules and other data for the computer 20. It should be appreciated bythose skilled in the art that any type of computer-readable media whichcan store data that is accessible by a computer, such as magneticcassettes, flash memory cards, digital video disks, Bernoullicartridges, random access memories (RAMs), read only memories (ROMs),redundant arrays of independent disks (e.g., RAID storage devices) andthe like, can be used in the exemplary operating environment.

A plurality of program modules can be stored on the hard disk, magneticdisk 29, optical disk 31, ROM 24, or RAM 25, including an operatingsystem 35, one or more application programs 36, other program modules37, and program data 38. A plug in containing a security transmissionengine for the present invention can be resident on any one or number ofthese computer-readable media.

A user may enter commands and information into computer 20 through inputdevices such as a keyboard 40 and pointing device 42. Other inputdevices (not shown) can include a microphone, joystick, game pad,satellite dish, scanner, or the like. These other input devices areoften connected to the processing unit 21 through a serial portinterface 46 that is coupled to the system bus 23, but can be connectedby other interfaces, such as a parallel port, game port, or a universalserial bus (USB). A monitor 47 or other type of display device can alsobe connected to the system bus 23 via an interface, such as a videoadapter 48. The monitor 40 can display a graphical user interface forthe user. In addition to the monitor 40, computers typically includeother peripheral output devices (not shown), such as speakers andprinters.

The computer 20 may operate in a networked environment using logicalconnections to one or more remote computers or servers, such as remotecomputer 49. These logical connections are achieved by a communicationdevice coupled to or a part of the computer 20; the invention is notlimited to a particular type of communications device. The remotecomputer 49 can be another computer, a server, a router, a network PC, aclient, a peer device or other common network node, and typicallyincludes many or all of the elements described above I/O relative to thecomputer 20, although only a memory storage device 50 has beenillustrated. The logical connections depicted in FIG. 6 include a localarea network (LAN) 51 and/or a wide area network (WAN) 52. Suchnetworking environments are commonplace in office networks,enterprise-wide computer networks, intranets and the internet, which areall types of networks.

When used in a LAN-networking environment, the computer 20 is connectedto the LAN 51 through a network interface or adapter 53, which is onetype of communications device. In some embodiments, when used in aWAN-networking environment, the computer 20 typically includes a modem54 (another type of communications device) or any other type ofcommunications device, e.g., a wireless transceiver, for establishingcommunications over the wide-area network 52, such as the internet. Themodem 54, which may be internal or external, is connected to the systembus 23 via the serial port interface 46. In a networked environment,program modules depicted relative to the computer 20 can be stored inthe remote memory storage device 50 of remote computer, or server 49. Itis appreciated that the network connections shown are exemplary andother means of, and communications devices for, establishing acommunications link between the computers may be used including hybridfiber-coax connections, T1-T3 lines, DSL's, OC-3 and/or OC-12, TCP/IP,microwave, wireless application protocol, and any other electronic mediathrough any suitable switches, routers, outlets and power lines, as thesame are known and understood by one of ordinary skill in the art.

Example Embodiments

Several embodiments and sub-embodiments have been disclosed above, andit is envisioned that any embodiment can be combined with any otherembodiment or sub-embodiment. Specific examples of such combinations areillustrated in the examples below.

Example No. 1 is a system including one or more of a computer processorand a computer storage device configured to store a map of an area, themap comprising objects in the area; identify objects on the map andlocations of the objects on the map; associate properties to theidentified objects; and provide the identified objects, the locations ofthe identified objects, and the properties of the identified objects toa radio frequency (RF) planning tool such that the RF planning tool candetermine RF wave propagation and RF wave attenuation as a function ofthe identified objects, the locations of the identified objects, and theproperties of the identified objects.

Example No. 2 includes all the features of Example No. 1, and optionallyincludes a system wherein the RF planning tool uses the identifiedobjects, the locations of the identified objects, and the properties ofthe identified objects in a link budget calculation.

Example No. 3 includes all the features of Example Nos. 1-2, andoptionally includes a system wherein the RF planning tool uses theidentified objects, the locations of the identified objects, and theproperties of the identified objects in a design of a wireless networkfor the area.

Example No. 4 includes all the features of Example Nos. 1-3, andoptionally includes a system wherein the map comprises one or more ofcomputer aided design (CAD) data, building information model (BIM) data,Internet-based map data, and jpeg data.

Example No. 5 includes all the features of Example Nos. 1-4, andoptionally includes a system wherein the computer processor isconfigured to receive input from a user to modify the properties of theidentified objects.

Example No. 6 includes all the features of Example Nos. 1-5, andoptionally includes a system wherein the computer processor isconfigured to identify the objects by tagging the objects, the taggingcomprising associating icons with the locations of the objects on themap and a size or area of the identified objects.

Example No. 7 includes all the features of Example Nos. 1-6, andoptionally includes a system wherein the computer processor isconfigured to receive input from a user relating to one or more ofshapes, colors, and patterns of the objects, and to use the user inputto identify the objects on the map.

Example No. 8 includes all the features of Example Nos. 1-7, andoptionally includes a system wherein the user input comprises one ormore of an Internet-based map, a computer aided design (CAD) format withsite specific details, and a building information model (BIM) formatwith site specific details.

Example No. 9 includes all the features of Example Nos. 1-8, andoptionally includes a system wherein the computer processor comprises apattern recognition algorithm to identify the objects.

Example No. 10 includes all the features of Example Nos. 1-9, andoptionally includes a system wherein the computer processor comprises atagging rule to identify the objects.

Example No. 11 includes all the features of Example Nos. 1-10, andoptionally includes a system wherein the computer processor isconfigured to receive input from a user and to use the user input toverify the identified objects.

Example No. 12 includes all the features of Example Nos. 1-11, andoptionally includes a system wherein the user input comprises one ormore of an Internet-based map, a computer aided design (CAD) format withsite specific details, and a building information model (BIM) formatwith site specific details.

Example No. 13 includes all the features of Example Nos. 1-12, andoptionally includes a system wherein the computer processor isconfigured to classify the identified objects as a function of one ormore of similar objects and similar materials.

Example No. 14 includes all the features of Example Nos. 1-13, andoptionally includes a system wherein the computer storage devicecomprises data relating to the identity of objects and the properties ofobjects, and the computer processor is configured to use the data toidentify objects in the area and to associate properties to theidentified objects.

Example No. 15 is a process including storing a map of an area in one ormore of a computer processor and a computer storage device, the mapcomprising objects in the area; identifying objects on the map andlocations of the objects on the map; associating properties to theidentified objects; and providing the identified objects, the locationsof the identified objects, and the properties of the identified objectsto a radio frequency (RF) planning tool such that the RF planning toolcan determine RF wave propagation and RF wave attenuation as a functionof the identified objects, the locations of the identified objects, andthe properties of the identified objects.

Example No. 16 includes all the features of Example No. 15, andoptionally includes a process wherein the RF planning tool uses theidentified objects, the locations of the identified objects, and theproperties of the identified objects in one or more of a link budgetcalculation, a design of a wireless network, an RF wave propagationmodeling of the wireless network, and an estimation of a link qualitybetween nodes in the wireless network.

Example No. 17 includes all the features of Example Nos. 15-16, andoptionally includes a process wherein the computer processor isconfigured to receive input from a user relating to one or more ofshapes, colors, patterns, and attributes of the objects, and to use theuser input to identify the objects on the map; and wherein the userinput comprises one or more of an Internet-based map, a computer aideddesign (CAD) format with site specific details, and a buildinginformation model (BIM) format with site specific details.

Example No. 18 includes all the features of Example Nos. 15-17, andoptionally includes a process wherein the computer processor isconfigured to receive input from a user and to use the user input toverify the identified objects; and wherein the user input comprises oneor more of an Internet-based map, a computer aided design (CAD) formatwith site specific details, and a building information model (BIM)format with site specific details.

Example No. 19 is a computer readable storage device comprisinginstructions that when executed by a processor execute a processcomprising storing a map of an area in one or more of a computerprocessor and a computer storage device, the map comprising objects inthe area; identifying objects on the map and locations of the objects onthe map; associating properties to the identified objects; and providingthe identified objects, the locations of the identified objects, and theproperties of the identified objects to a radio frequency (RF) planningtool such that the RF planning tool can determine RF wave propagationand RF wave attenuation as a function of the identified objects, thelocations of the identified objects, and the properties of theidentified objects.

Example No. 20 includes all the features of Example No. 19, andoptionally includes a computer readable storage device wherein theidentifying of the objects and the locations of the objects is automaticas a function of a maturation of a system comprising the computerreadable storage device and a learning of patterns by the system.

It should be understood that there exist implementations of othervariations and modifications of the invention and its various aspects,as may be readily apparent, for example, to those of ordinary skill inthe art, and that the invention is not limited by specific embodimentsdescribed herein. Features and embodiments described above may becombined with each other in different combinations. It is thereforecontemplated to cover any and all modifications, variations,combinations or equivalents that fall within the scope of the presentinvention.

The Abstract is provided to comply with 37 C.F.R. §1.72(b) and willallow the reader to quickly ascertain the nature and gist of thetechnical disclosure. It is submitted with the understanding that itwill not be used to interpret or limit the scope or meaning of theclaims.

In the foregoing description of the embodiments, various features aregrouped together in a single embodiment for the purpose of streamliningthe disclosure. This method of disclosure is not to be interpreted asreflecting that the claimed embodiments have more features than areexpressly recited in each claim. Rather, as the following claimsreflect, inventive subject matter lies in less than all features of asingle disclosed embodiment. Thus the following claims are herebyincorporated into the Description of the Embodiments, with each claimstanding on its own as a separate example embodiment.

1. A system comprising: one or more of a computer processor and acomputer storage device configured to: store a map of an area, the mapcomprising objects in the area; identify objects on the map andlocations of the objects on the map; associate properties to theidentified objects; and provide the identified objects, the locations ofthe identified objects, and the properties of the identified objects toa radio frequency (RF) planning tool such that the RF planning tool candetermine RF wave propagation and RF wave attenuation as a function ofthe identified objects, the locations of the identified objects, and theproperties of the identified objects.
 2. The system of claim 1, whereinthe RF planning tool uses the identified objects, the locations of theidentified objects, and the properties of the identified objects in alink budget calculation.
 3. The system of claim 1, wherein the RFplanning tool uses the identified objects, the locations of theidentified objects, and the properties of the identified objects in adesign of a wireless network for the area.
 4. The system of claim 1,wherein the map comprises one or more of computer aided design (CAD)data, building information model (BIM) data, Internet-based map data,and jpeg data.
 5. The system of claim 1, wherein the computer processoris configured to receive input from a user to modify the properties ofthe identified objects.
 6. The system of claim 1, wherein the computerprocessor is configured to identify the objects by tagging the objects,the tagging comprising associating icons with the locations of theobjects on the map and a size or area of the identified objects.
 7. Thesystem of claim 1, wherein the computer processor is configured toreceive input from a user relating to one or more of shapes, colors, andpatterns of the objects, and to use the user input to identify theobjects on the map.
 8. The system of claim 7, wherein the user inputcomprises one or more of an Internet-based map, a computer aided design(CAD) format with site specific details, and a building informationmodel (BIM) format with site specific details.
 9. The system of claim 1,wherein the computer processor comprises a pattern recognition algorithmto identify the objects.
 10. The system of claim 1, wherein the computerprocessor comprises a tagging rule to identify the objects.
 11. Thesystem of claim 1, wherein the computer processor is configured toreceive input from a user and to use the user input to verify theidentified objects.
 12. The system of claim 11, wherein the user inputcomprises one or more of an Internet-based map, a computer aided design(CAD) format with site specific details, and a building informationmodel (BIM) format with site specific details.
 13. The system of claim1, wherein the computer processor is configured to classify theidentified objects as a function of one or more of similar objects andsimilar materials.
 14. The system of claim 1, wherein the computerstorage device comprises data relating to the identity of objects andthe properties of objects, and the computer processor is configured touse the data to identify objects in the area and to associate propertiesto the identified objects.
 15. A process comprising: storing a map of anarea in one or more of a computer processor and a computer storagedevice, the map comprising objects in the area; identifying objects onthe map and locations of the objects on the map; associating propertiesto the identified objects; and providing the identified objects, thelocations of the identified objects, and the properties of theidentified objects to a radio frequency (RF) planning tool such that theRF planning tool can determine RF wave propagation and RF waveattenuation as a function of the identified objects, the locations ofthe identified objects, and the properties of the identified objects.16. The process of claim 15, wherein the RF planning tool uses theidentified objects, the locations of the identified objects, and theproperties of the identified objects in one or more of a link budgetcalculation, a design of a wireless network, an RF wave propagationmodeling of the wireless network, and an estimation of a link qualitybetween nodes in the wireless network.
 17. The process of claim 15,wherein the computer processor is configured to receive input from auser relating to one or more of shapes, colors, patterns, and attributesof the objects, and to use the user input to identify the objects on themap; and wherein the user input comprises one or more of anInternet-based map, a computer aided design (CAD) format with sitespecific details, and a building information model (BIM) format withsite specific details.
 18. The process of claim 15, wherein the computerprocessor is configured to receive input from a user and to use the userinput to verify the identified objects; and wherein the user inputcomprises one or more of an Internet-based map, a computer aided design(CAD) format with site specific details, and a building informationmodel (BIM) format with site specific details.
 19. A computer readablestorage device comprising instructions that when executed by a processorexecute a process comprising: storing a map of an area in one or more ofa computer processor and a computer storage device, the map comprisingobjects in the area; identifying objects on the map and locations of theobjects on the map; associating properties to the identified objects;and providing the identified objects, the locations of the identifiedobjects, and the properties of the identified objects to a radiofrequency (RF) planning tool such that the RF planning tool candetermine RF wave propagation and RF wave attenuation as a function ofthe identified objects, the locations of the identified objects, and theproperties of the identified objects.
 20. The computer readable storagedevice of claim 19, wherein the identifying of the objects and thelocations of the objects is automatic as a function of a maturation of asystem comprising the computer readable storage device and a learning ofpatterns by the system.